carla
open_spiel
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carla | open_spiel | |
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22 | 44 | |
10,491 | 3,999 | |
2.6% | 1.5% | |
8.3 | 9.5 | |
4 days ago | 2 days ago | |
C++ | C++ | |
MIT License | Apache License 2.0 |
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carla
- Tesla braces for its first trial involving Autopilot fatality
- Mediocre Arduino Coder here: is there anyone that can offer their expertise on a virtual autonomous car project?
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Best Self Driving Cars Projects.
It sounds like you're looking for something like the CARLA simulator.
- What good Autonomous Driving simulators for research?
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Importing map from google maps
If you are looking for a different simulator, I would suggest using (Carla)[https://carla.org/] with ROS bridge and it also has an inbuilt support for OSM which worked flawlessly (you have to install it from source to get the OSM plugin).
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[D] Doing my (bachelor) thesis on RL. Which topic do you like best?
(3) I would suggest you use CARLA or TORCS for self-driving cars in RL as they are common test beds.
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Can someone build carla RL env for centOS for me?
carla env
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Car simulation RL environment - Carla centOS build
Link to carla
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Best way to simulate and train VSLAM based robot in virtual environments?
There are a few ways you could go with this. A fun recent trend has been to make simulators in the unreal engine for photorealistic training. If you wanted to spend your whole project on the simulator part you could make your own environment, but I highly recommend using an open-source sim package. If you don't care too much about photorealism, you could use gazebo just fine. I've also made small visual worlds in blender, then simulated with RVIZ. Here's a good one with a focus on aerial robotics: https://theairlab.org/tartanair-dataset/ You could also give CARLA a spin for autonomous vehicles: https://carla.org/
- Open-source simulator for autonomous driving research
open_spiel
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What projects or open-source contributions can impress Jane Street recruiters for a Quant SWE role ?
Deep mind actually has a repository where they applied this algorithm for incomplete-knowledge games. You could use it for reference: https://github.com/deepmind/open_spiel/tree/master/open_spiel/python/algorithms
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I want to build a learning agent for a combinatorial game
+1. You can also find an implementation of Clobber and AlphaZero (and many other basic RL algorithms) in OpenSpiel: https://github.com/deepmind/open_spiel
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minimax for imperfect-information turn-games?
You can find a lot of code online if you look, and many of these applied to Poker. There's a general implementation of both in Python and C++ in OpenSpiel, with some examples applied to small poker games. It's nice code to learn from because the algorithms operate over generic game descriptions, so there aren't game-specific design choices mixed up with the implementation of the algorithms, and you can create your own poker game and just run them on it.
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OpenSpiel 1.3 Released!
And many other additions and improvements. See all the details here: https://github.com/deepmind/open_spiel/releases/tag/v1.3
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What's a good OpenAI Gym Environment for applying centralized multi-agent learning using expected SARSA with tile coding?
I would checkout the openspiel package. It's main focus is RL in games (multi-agent environments). You'll find RL examples there and games that are small enough to solve without deep RL. There's also a wide range of environments from fully cooperative to adversarial zero-sum.
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Competitive reinforcement learning for turn-based games
Hi, you can check out OpenSpiel: https://github.com/deepmind/open_spiel/
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Reinforcement learning and Game Theory a turn-based game
as for algorithms , openspiel repository has few implementations some of these are not related to imperfect information games , and others are not for multiagent environment and others are tabular algorithms .
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Shimmy 1.0: Gymnasium & PettingZoo bindings for popular external RL environments
This includes single-agent Gymnasium wrappers for DM Control, DM Lab, Behavior Suite, Arcade Learning Environment, OpenAI Gym V21 & V26. Multi-agent PettingZoo wrappers support DM Control Soccer, OpenSpiel and Melting Pot. For more information, read the release notes here:
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How to deal with situations where the RL agent cannot act at every time step?
I've had some success using Action Masking - you can refer to here https://github.com/deepmind/open_spiel/blob/120420a74a69354d64c10b51cd129d4587f9f325/open_spiel/python/algorithms/dqn.py but for DQN you need to mask out q values for invalid actions (as well as masking them during prediction). In my case I'm able to place my mask in the observation so can fetch it quite easily during prediction but if that's not possible you could query it from the environment and store it in the replay buffer (like they do in the link I shared)
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How to search the game tree with depth-first search?
Take a look at this simple implementation: https://github.com/deepmind/open_spiel/blob/master/open_spiel/algorithms/minimax.cc
What are some alternatives?
AirSim - Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
muzero-general - MuZero
simulator - A ROS/ROS2 Multi-robot Simulator for Autonomous Vehicles
PettingZoo - An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
openpilot - openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for 250+ supported car makes and models.
gym - A toolkit for developing and comparing reinforcement learning algorithms.
apollo - An open autonomous driving platform
rlcard - Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.
webots - Webots Robot Simulator
gym-battleship - Battleship environment for reinforcement learning tasks
TexasHoldemSolverJava - A Java implemented Texas holdem and short deck Solver